Semrush says agencies must optimize for AI search visibility now

AI search is no longer a side experiment that agencies can ignore until next quarter. Semrush is reframing generative engine optimization as a core service-line shift, because the goal is no longer just to rank on a results page, it is to appear inside the answer the user actually receives.

GEO changes what agencies are selling

Semrush’s guide makes the key distinction plain: GEO is the practice of optimizing content and brand presence so it shows up in responses generated by AI-powered search systems such as ChatGPT, Google, Perplexity, Claude, and similar tools. That is a different business problem from classic SEO. A page can rank well and still fail to appear in the AI-generated response that now shapes what people read, trust, and act on.

That shift matters because AI systems are behaving more like answer engines and task-completion systems than classic search engines. For agencies, that means visibility is no longer measured only by position on a search engine results page. It is measured by whether the model selects, synthesizes, and surfaces the brand when it constructs the final answer.

SEO still matters, but it is no longer enough

Semrush is careful not to present GEO as a replacement for SEO. Crawlability, keyword relevance, and backlinks still matter, and agencies that forget those fundamentals will still lose. But the guide also makes clear that AI systems reward a wider set of signals, including clarity, extractability, fresh information, and credible mentions across the web.

That is where the service model changes. Traditional SEO reporting often centers on rankings, impressions, and clicks. GEO forces agencies to think about whether content is easy for models to parse, whether the brand is recognized as a trustworthy source, and whether the surrounding web ecosystem reinforces that authority. In practice, that means content strategy, digital PR, technical SEO, and authority-building can no longer operate as separate workstreams.

The underlying research shows why this is not hype

The GEO concept did not appear out of nowhere. The 2024 KDD paper, GEO: Generative Engine Optimization, formalized the idea that generative engines synthesize information from multiple sources and summarize it using large language models. The paper also argued that creators have limited control over when and how their content appears inside those answers, which is exactly why optimization has to happen upstream.

Just as important, the paper reported that GEO methods can boost visibility by up to 40% in generative engine responses. It also found that effectiveness varies by domain, which points to a practical reality agencies cannot ignore: there is no universal GEO playbook that works equally well for every client. A strategy that helps one sector surface in AI answers may underperform in another, so agencies need domain-specific testing rather than a one-size-fits-all checklist.

Why ranking reports are starting to miss the real outcome

The biggest weakness in old-school reporting is that it assumes the click is still the main signal of success. Pew Research found that in March 2025, 58% of tracked U.S. Google users conducted at least one search that produced an AI-generated summary. In those results, users were less likely to click on result links, and they very rarely clicked sources cited inside the summaries.

Pew’s broader browsing analysis reinforces how normal these interfaces have become, with around six-in-ten respondents visiting a search page that included an AI-generated summary during the study period. That means agencies cannot rely on ranking reports alone to explain visibility. A client may see steady positions and still lose attention if the AI summary answers the query before the organic listing gets a chance.

What a GEO service line should actually include

A serious GEO offering is broader than content refreshes or prompt testing. It should be built around the idea that the model has to understand the brand, trust the source, and extract the right information quickly. That pushes agencies into a fuller stack of work, where technical, editorial, and reputation signals all need to line up.

Core deliverables agencies should build into GEO

• Content architecture that makes key facts easy to extract, with concise definitions, clear headings, and direct answers.

• Digital PR and mention-building that helps establish credible references elsewhere on the web.

• Technical SEO improvements that keep pages crawlable, indexable, and well-structured for machine interpretation.

• Freshness programs that keep core pages current, since AI systems reward newer and more reliable information.

• Domain-specific testing that checks how the brand appears across query classes, not just across keyword sets.

This is the practical evolution Semrush is pointing toward. Agencies are not just optimizing pages, they are shaping the information environment the model sees before it generates an answer.

The KPI mix has to change too

If the objective changes, the measurement has to change with it. A GEO dashboard should still track conventional SEO inputs, but it also needs new visibility metrics that reflect answer engines instead of blue links. The most useful KPIs are the ones that show whether the brand is appearing inside the AI layer at all.

Better GEO KPIs for agencies

• Share of answer, meaning how often the brand appears in AI-generated responses for target prompts.

• Citation rate, meaning how often the model references the client’s pages or trusted third-party coverage.

• Mention consistency across question types, since different domains respond differently and the KDD paper showed GEO effectiveness varies by domain.

• Freshness and extractability scores for core pages, especially for pages intended to feed answers rather than just attract clicks.

• Assisted visibility, which looks at whether AI exposure supports downstream traffic, leads, or conversions even when the click happens later.

That kind of reporting gives agencies something ranking reports cannot: proof that the brand is part of the answer, not just part of the index.

The demand curve is moving faster than most agency teams expected

Semrush’s own July 2025 study argues that AI search visitors could surpass traditional search visitors for digital marketing and SEO topics by early 2028. That is a serious forecast for any agency that makes its living from organic visibility. It also helps explain why the company says marketers need to care now rather than later.

The usage numbers around ChatGPT point in the same direction. Semrush said weekly active users grew 8x from October 2023 to April 2025 and exceeded 800 million. OpenAI’s February 2026 consumer usage analysis, meanwhile, is based on messages sent between July 2024 and the end of 2025, and it distinguishes between work-related and non-work-related use. That split matters because it shows AI is not just a novelty for side tasks, but a mainstream behavior pattern that spans both professional and personal contexts.

The agency opportunity is bigger than a keyword trend

The best way to read Semrush’s guide is as a warning and a roadmap. Agencies that treat GEO like a buzzword will keep producing the same reports and wondering why clients ask harder questions about visibility. Agencies that treat it as a service-line evolution can build a more relevant offering, one that connects content, technical health, authority, and digital PR to the way AI systems actually present information.

That is the real shift here. GEO is not about chasing a new acronym, it is about proving visibility inside the answer layer where discovery is increasingly happening. For agencies, the winners will be the ones that can show clients not just where they rank, but where they appear when the search engine becomes the source of the answer.